{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "QQHZHevuXdEy"
      },
      "source": [
        "# **QSAR Model prediciton of unknown Inhibitors**\n",
        "\n",
        "Chanin Nantasenamat\n",
        "\n",
        "*Data Professor YouTube channel, http://youtube.com/dataprofessor*\n",
        "\n",
        "*Modified by quantaosun@gmail.com*"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "g1qtHa0zXfWM"
      },
      "source": [
        "# Read in data"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "id": "9MdfbvFKXtXq"
      },
      "outputs": [],
      "source": [
        "import pandas as pd"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Change here for local or public data\n",
        "\n"
      ],
      "metadata": {
        "id": "Fnv-6xfx4bdl"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 488
        },
        "id": "nerGP0fCXfgP",
        "outputId": "d6422de9-a1ef-4cdb-da60-79e5d0d3910b"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "      <td>1</td>\n",
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              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
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              "    <tr>\n",
              "      <th>134</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
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              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <th>135</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
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              "      <td>0</td>\n",
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              "      <td>0</td>\n",
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              "      <td>0</td>\n",
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              "      <td>0</td>\n",
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              "      <td>0</td>\n",
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              "      <td>1</td>\n",
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              "      <td>1</td>\n",
              "      <td>1</td>\n",
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              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
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              "      <td>0</td>\n",
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              "      <td>0</td>\n",
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              "      <td>1</td>\n",
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              "      <td>1</td>\n",
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              "      <td>1</td>\n",
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              "      <td>1</td>\n",
              "      <td>1</td>\n",
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              "          document.querySelector('#df-1214b913-618a-48e7-8f98-07007f552813 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-1214b913-618a-48e7-8f98-07007f552813');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "     PubchemFP0  PubchemFP1  PubchemFP2  ...  PubchemFP879  PubchemFP880     pIC50\n",
              "0             1           1           1  ...             0             0  6.721246\n",
              "1             1           0           0  ...             0             0  4.873869\n",
              "2             1           1           0  ...             0             0  6.045757\n",
              "3             1           1           1  ...             0             0  6.552842\n",
              "4             1           1           0  ...             0             0  4.552842\n",
              "..          ...         ...         ...  ...           ...           ...       ...\n",
              "134           1           1           1  ...             0             0  6.397940\n",
              "135           1           1           1  ...             0             0  4.934047\n",
              "136           1           1           1  ...             0             0  4.706637\n",
              "137           1           1           1  ...             0             0  4.665144\n",
              "138           1           1           1  ...             0             0  4.524765\n",
              "\n",
              "[139 rows x 882 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 2
        }
      ],
      "source": [
        "dataset = pd.read_csv('/content/sars-cov-2_bioactivity_data_2class_pIC50_pubchem_fp.csv')\n",
        "dataset"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 488
        },
        "id": "tgFxx8m_YEUy",
        "outputId": "973afbe2-fd50-4516-8627-045baba3b4d9"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
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              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
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              "      <th>PubchemFP0</th>\n",
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              "    <tr>\n",
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              "      <td>1</td>\n",
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              "      <th>138</th>\n",
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              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>139 rows × 881 columns</p>\n",
              "</div>\n",
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              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "      flex-wrap:wrap;\n",
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              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
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              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-49b38e99-a1aa-40d0-97a8-cd49c79e425d button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-49b38e99-a1aa-40d0-97a8-cd49c79e425d');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "     PubchemFP0  PubchemFP1  ...  PubchemFP879  PubchemFP880\n",
              "0             1           1  ...             0             0\n",
              "1             1           0  ...             0             0\n",
              "2             1           1  ...             0             0\n",
              "3             1           1  ...             0             0\n",
              "4             1           1  ...             0             0\n",
              "..          ...         ...  ...           ...           ...\n",
              "134           1           1  ...             0             0\n",
              "135           1           1  ...             0             0\n",
              "136           1           1  ...             0             0\n",
              "137           1           1  ...             0             0\n",
              "138           1           1  ...             0             0\n",
              "\n",
              "[139 rows x 881 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 3
        }
      ],
      "source": [
        "X = dataset.drop(['pIC50'], axis=1)\n",
        "X"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "X.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "64RJ8G252sT8",
        "outputId": "23f621e7-333f-43b8-9bb2-8743c763f025"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(139, 255)"
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "JDwxgKHqYmD4",
        "outputId": "777dfc52-c035-464b-fb16-21e5cd9e165b"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0      6.721246\n",
              "1      4.873869\n",
              "2      6.045757\n",
              "3      6.552842\n",
              "4      4.552842\n",
              "         ...   \n",
              "134    6.397940\n",
              "135    4.934047\n",
              "136    4.706637\n",
              "137    4.665144\n",
              "138    4.524765\n",
              "Name: pIC50, Length: 139, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 4
        }
      ],
      "source": [
        "Y = dataset.iloc[:,-1]\n",
        "Y"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "Y.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "xFGnM4ZS2oNF",
        "outputId": "2d8e28d4-b893-4447-c9d9-56c84902b4a0"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(139,)"
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "AQ9E0xUY_o_M"
      },
      "source": [
        "# Remove low variance features"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 488
        },
        "id": "Qkgj-lsG_wOJ",
        "outputId": "35fbe4c6-61fc-44bd-fbfa-2c6c8c9cc118"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
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              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>PubchemFP2</th>\n",
              "      <th>PubchemFP3</th>\n",
              "      <th>PubchemFP13</th>\n",
              "      <th>PubchemFP15</th>\n",
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              "      <th>PubchemFP19</th>\n",
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              "      <th>PubchemFP180</th>\n",
              "      <th>PubchemFP181</th>\n",
              "      <th>PubchemFP185</th>\n",
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              "      <th>PubchemFP797</th>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>134</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>135</th>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>136</th>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>137</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>138</th>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
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              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>139 rows × 255 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-d4698f52-a8e6-4455-a774-559b74b703e9')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
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              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
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              "      gap: 12px;\n",
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              "\n",
              "    .colab-df-convert {\n",
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              "      border-radius: 50%;\n",
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              "      fill: #1967D2;\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
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              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
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              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-d4698f52-a8e6-4455-a774-559b74b703e9 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-d4698f52-a8e6-4455-a774-559b74b703e9');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
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              "          await google.colab.output.renderOutput(dataTable, element);\n",
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              "  "
            ],
            "text/plain": [
              "     PubchemFP2  PubchemFP3  ...  PubchemFP819  PubchemFP821\n",
              "0             1           1  ...             1             0\n",
              "1             0           0  ...             1             0\n",
              "2             0           0  ...             1             0\n",
              "3             1           1  ...             1             0\n",
              "4             0           0  ...             0             0\n",
              "..          ...         ...  ...           ...           ...\n",
              "134           1           1  ...             0             1\n",
              "135           1           0  ...             0             0\n",
              "136           1           0  ...             0             0\n",
              "137           1           1  ...             0             0\n",
              "138           1           0  ...             0             0\n",
              "\n",
              "[139 rows x 255 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 5
        }
      ],
      "source": [
        "from sklearn.feature_selection import VarianceThreshold\n",
        "\n",
        "def remove_low_variance(input_data, threshold=0.1):\n",
        "    selection = VarianceThreshold(threshold)\n",
        "    selection.fit(input_data)\n",
        "    return input_data[input_data.columns[selection.get_support(indices=True)]]\n",
        "\n",
        "X = remove_low_variance(X, threshold=0.1)\n",
        "X"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "X.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "STRQK0pp2xrU",
        "outputId": "27b099ee-18a4-4aff-9292-cd16b68df861"
      },
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(139, 255)"
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "metadata": {
        "id": "SVOdbTiuDru1"
      },
      "outputs": [],
      "source": [
        "X.to_csv('descriptor_list.csv', index = False)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 488
        },
        "id": "0vJWboCKDru2",
        "outputId": "9dd67f45-ade8-4676-90dd-e2bca314fc15"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>...</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>134</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>135</th>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>136</th>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>137</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>138</th>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>139 rows × 255 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-11d8353b-ffd4-4103-bd29-2b70757df7a7')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-11d8353b-ffd4-4103-bd29-2b70757df7a7 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-11d8353b-ffd4-4103-bd29-2b70757df7a7');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "     PubchemFP2  PubchemFP3  ...  PubchemFP819  PubchemFP821\n",
              "0             1           1  ...             1             0\n",
              "1             0           0  ...             1             0\n",
              "2             0           0  ...             1             0\n",
              "3             1           1  ...             1             0\n",
              "4             0           0  ...             0             0\n",
              "..          ...         ...  ...           ...           ...\n",
              "134           1           1  ...             0             1\n",
              "135           1           0  ...             0             0\n",
              "136           1           0  ...             0             0\n",
              "137           1           1  ...             0             0\n",
              "138           1           0  ...             0             0\n",
              "\n",
              "[139 rows x 255 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ],
      "source": [
        "# In the app, use the following to get this same descriptor list\n",
        "# of 218 variables from the initial set of 881 variables\n",
        "Xlist = list(pd.read_csv('descriptor_list.csv').columns)\n",
        "X[Xlist]"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "LNohCdqQY5VZ"
      },
      "source": [
        "# Random Forest Regression Model"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 8,
      "metadata": {
        "id": "EanoyG2eX9cV"
      },
      "outputs": [],
      "source": [
        "from sklearn.ensemble import RandomForestRegressor\n",
        "from sklearn.metrics import mean_squared_error, r2_score"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 9,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "mLQJ2KLLY_9a",
        "outputId": "ed2c60f2-ac10-44ff-f671-693fe6a36735"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.8364878751929994"
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ],
      "source": [
        "model = RandomForestRegressor(n_estimators=500, random_state=42)\n",
        "model.fit(X, Y)\n",
        "r2 = model.score(X, Y)\n",
        "r2"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "Y_pred = model.predict(X)"
      ],
      "metadata": {
        "id": "g-othcbt2RHA"
      },
      "execution_count": 13,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "Y_pred"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "oafpGZZP2RN9",
        "outputId": "8b201379-fe7a-4fbc-982f-c485eed4a0c1"
      },
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([6.21029889, 4.95306765, 5.65376784, 6.0737454 , 4.85508445,\n",
              "       5.55043843, 5.40866091, 4.91139887, 4.58607266, 4.74251134,\n",
              "       4.92358882, 4.58607266, 5.40866091, 4.67391146, 4.94225041,\n",
              "       4.74251134, 4.91634124, 6.85529578, 6.84934313, 6.63446636,\n",
              "       6.145992  , 6.52697961, 6.09608432, 6.26425444, 6.42247503,\n",
              "       5.97095897, 6.18262185, 5.88827387, 5.84763541, 5.9440147 ,\n",
              "       5.95083472, 5.55043843, 6.05152219, 5.60227032, 5.77199426,\n",
              "       5.73639183, 5.24059371, 4.97317061, 5.1718789 , 5.17657733,\n",
              "       4.95592296, 5.00088593, 4.99674216, 4.85140441, 4.97311073,\n",
              "       5.21316581, 5.11168449, 5.03047623, 4.98107221, 4.86404144,\n",
              "       4.83894204, 5.40386421, 4.7592848 , 4.85981719, 5.02424057,\n",
              "       4.89602972, 4.82994587, 4.67391146, 5.76569579, 6.32986357,\n",
              "       5.34683957, 6.22924296, 6.0194548 , 5.06898552, 4.45100306,\n",
              "       6.19878081, 5.11789912, 7.28625885, 6.06608736, 6.22438797,\n",
              "       5.04350147, 5.2046339 , 6.07804458, 6.27250334, 6.62302893,\n",
              "       5.13633501, 5.18923981, 5.03261173, 6.52309016, 4.88960743,\n",
              "       6.92517808, 5.1500697 , 4.92756591, 5.247626  , 5.03302182,\n",
              "       4.89596405, 4.83293793, 6.14437196, 4.96030616, 5.67008319,\n",
              "       5.37495446, 4.93118969, 5.02230074, 4.99854532, 5.40386421,\n",
              "       6.20973696, 5.08428309, 4.89395297, 5.17604646, 5.10045081,\n",
              "       6.84012945, 5.17999037, 6.27098683, 6.27098683, 4.94884853,\n",
              "       5.17850282, 6.22317639, 5.26240514, 5.1374477 , 6.09701318,\n",
              "       6.09701318, 4.94607759, 5.04200211, 6.56377803, 4.73208244,\n",
              "       5.0074056 , 4.78895823, 5.84700205, 5.00664673, 6.00984053,\n",
              "       5.17755178, 4.91139887, 4.89612328, 5.03668036, 4.95768115,\n",
              "       5.60227032, 4.8618483 , 5.13729376, 4.99917003, 4.80364367,\n",
              "       6.23622244, 5.99102469, 5.23935882, 4.92405917, 5.93801266,\n",
              "       5.11670684, 4.87567912, 5.10003527, 4.78428262])"
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import seaborn as sns\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "sns.set(color_codes=True)\n",
        "sns.set_style(\"white\")\n",
        "\n",
        "ax = sns.regplot(Y, Y_pred, scatter_kws={'alpha':0.4})\n",
        "ax.set_xlabel('Experimental pIC50', fontsize='large', fontweight='bold')\n",
        "ax.set_ylabel('Predicted pIC50', fontsize='large', fontweight='bold')\n",
        "ax.set_xlim(0, 12)\n",
        "ax.set_ylim(0, 12)\n",
        "ax.figure.set_size_inches(5, 5)\n",
        "plt.show"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 416
        },
        "id": "58f4W39E3T-L",
        "outputId": "cc3a12a6-c31a-4ec6-a291-1c2932d9300a"
      },
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/seaborn/_decorators.py:43: FutureWarning: Pass the following variables as keyword args: x, y. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
            "  FutureWarning\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<function matplotlib.pyplot.show>"
            ]
          },
          "metadata": {},
          "execution_count": 16
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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mw+sxKCqtbud3JK3tmKHadJXU8WgVlZyKGg/7HXYrFqChwUfWnlIG9Izznws1DFzhdmrrPOzOL+dQZX3gtZ0iHQwb0JUze/tn8D0eA3dNgy7mPw0cM1SnTp0a1DpjraKSU1XjYX+f1Biycg7h8/koq6pn3Rd76dLZRXKii+27S9iUdZCaOg/gXxH108HdGHlOGpu+PkhFVT2ucHvgMik1kz71tXj4r1VUcqo4kds67yuqZN3mvazbvBeH3UpMlJPaBg8HS2qwWixEhNlI7BzBpq8PUlR2eEWU3cqgXvH0TYlhxDlppHXtRESYXZdJnYaOGapNV1EVFRUxd+5cMjMzueyyywB47733+PDDD/nTn/7U+lWKnIQTua3zFzsLeP6dHRSW1eDxGlitUFRWjd1mJSYqDI/XR1lVHR9+lkfjmKNrnIuh/bvQKyWGs/rE0y3Bv09dJnV6OmaoNl1FNXPmTBISEvjLX/4S2JaZmcmoUaP44IMPuPzyy1u3SpGTcKzZ+4+/2EtMVHhg9JqcEMGyldkUldfisNuw2XxUuv0romrrfVTXejAgEKZWC8REOfmvgV35+QVnKEAFgKD6iX3yySe43W7q6uoC22pra6murubTTz9tteJEzFBaUYsrvPn4od7jYcvOImrrPCTEhFNb5+HNdd9RWlEHBjR4fNTX+zAg0EHKZ3wfqBYLdI2LIKVLFMWVtWzNLm7bNyUdVlCXVEVFRVFSUsIVV1zBRRddBMD69espLS0lIUHrk6Vja9rYpKyylvzCKr7dW4bTbqOkvJrv9jfgrmngYKkbd00dXp+B1WLFZ4DlcIg2nV1whduJjXRSWe2f7Q9z2Dl0uNuUSFChOnXqVB5//HFycnLIyckBvp/Euvrqq1uvOhETZKQnsHpjPuVVdew5UEG9x0tFVR1Ou5V1m/eRkujvCBXmsFHn8WEF6jz+2fymYWq3WYnrFEa9x0dxeQ0Wi4WaOi8Ou1WXSklAUKH629/+lpiYGBYvXsz+/fsB6NatG9OnT2fSpEmmFFJXV8eDDz7If/7zH8LCwsjIyGDevHmm7FtObymJ0YwansY/P/gGd62HmtoGXBEOqqob8Hp95B2swum0ERMVTl5BJfU/uOjFgv/cqcNho6zSv47fZvOHbIPXR4zLqY5SEhD0iqqJEycyceJEqqr8nXaioqJMLeSRRx4hLCyMlStXYrFYKC7WOSoxT0piNN0SoqipbaC6xv9VX+/BaoF6n8E3uYdwOW34fvC6cKeNmCgnVTUeKqprsAAOuwWPz8BqQM+kTlyR2UeTVBJwQstUt23bxpYtW4iOjmbMmDFUVFSQkJCA0+k8qSLcbjdvvvkmH3/8cWDBgc7VitmsFsgtqMTj8eEzDHwG+FeUGlh9BmUN30eqzWYhKS6C2jovJeW1+AwDp82K1+cjPMxOVISTs/rEc8XFClRpLqhQ9Xg8zJ49mw8//BCAIUOG4HK5mD17NnfccQfXX3/9SRWRn59PbGwsCxcuZOPGjURGRnLbbbcxbNiwk9qvSFMWi/+rutaDzWqh6doWX5PvYyL9l1+VVtbj9fq7THWOCie1SxTl7jrCnXYy0hO5eGiqAlWOENQlVU8//TSrVq3CMIzABNXFF1+MzWZj/fr1J12E1+slPz+fgQMHsnz5cu68805uueWWwKkGETN4fRDjcuIzDGrqvfxwvaDDbiWtSyQWiwV3rQfD58OCBafDRkJsGHUNXs47K5lZk85myqUDFKhyVEGF6ttvv43dbmfhwoWBbRERESQnJ7Nnz56TLiI5ORm73c7YsWMB/0i4c+fOgSsNRMxgs0JZVV3gBnyNLBb/ZVedXA4Ky2oIc9pw2q3+U1EWGNAzlhHDejBr0tlMHqMwlZYFdfi/f/9++vTpw6hRo5ptj4qK4sCBAyddRFxcHMOHD2fDhg1ccMEF5OTkUFJSQo8ePU563yKN3DUNVLgbAveIAogIsxMVYaeqpgHD5z8S654UjeEDm91Kr26dmDxmQDtWLaEmqFCNjo7mwIED1NZ+f4FzeXk5OTk5xMTEmFLIn/70J37/+98zf/587HY7Dz/8MJ06dTJl33J68/oM3v93Div+vQev13/Qb7dZiI0Oo67eS1FZLRb8k1OdIp2cMyAp0FXqop+ktm/xEnKCCtVhw4axevVqrrrqKsA/sTRhwgTq6uoCK6xOVlpaGi+88IIp+xJptOdABQtf3crO3EPA9+v1LRYLZZV1eA6HrMNhwRXmoFe3GHWVkpMSVKjefPPNrF+/nuzsbCwWC6WlpZSUlBAWFsaMGTNau0Y5xZ1IW75g1TV4efnDnSxf+y3ew1P7sVFOoiOdlFXWUlntaf4CA6JcDq6//EwFqZyUoCaq+vfvzwsvvMDw4cMJDw8nPDyc4cOH8/zzz9O/f//WrlFOYY1t+Zo2Nlm9MZ99RZU/ep/bdhVxy6NrefWjXXh9Bl3jXIz/WW/O7pdIfb0Hd43/on+r1b9aym6zEOa0kxQXqUCVkxb0xf+DBw/m+eefb81a5DTU2Javwetl+3fluGsasNutfPzF3hOeIKpw1/O/72zno035ANisFn5x/hlMHt2Pt/71HZHhkWTllGKxgK9xrsriv5TKFWYnMc5l8ruT01FQI9UBAwYwceLEI7bPnTv3qNtFglVaUUu9x0NWziEaPD6iIhxYgC07i4IerRqGwbrN+cyY/1EgUHunxPDnmRdww+VnEeVyEhsVhtNhJ8rlwGGzcvhqKWwWCw6bjYhwOz2SNDEqJy+okeqxbquyc+dOtm/fbmpBcnqJ6xTOluxCwpw2whw2ACz4Z+a3Zhcf93C8oMTN317/ki92FgIQEWbjqlH9GH9hLxyH9wffd6ryeCE2Ooyaei8WA2KinTR4DTxen5qiiClaDNU333wz8H1paWmzn91uN99++y12u+5yLX7BTDj98DnJCRGs21xHbHQYhmFQ3+CjrsFD/x6dW+xR6vX6eGv9dyxd+Q31Df6lpD/p14XfXn4W3boc2eynsVPVjpxiKtz+/fowKKuqJ9xpo3f32BbvWWX2RJqculpMxDlz5gQanOTn53PPPfcc8ZzevXu3TmUSUoK5D9TRnvPVrlK6dA5n994KKqrrsdssdEuMoqbOS9f4yKP+rl35h1j4yja+218O+Eee144dyIihaS3eATglMZrBfRNp+MY/MvV4fdhtVuw2a4uBGuz9rUQgiMN/wzCwWCxHPQUQFxfHXXfd1SqFSWg51n2gmh7CH+055VV17CtyU9fgJTY6DLvVQnFZDe7qeq4dN6jZ76ip8/DPD7J491/f+bvyA5nnpHHt2IHERAXXJNpigTCnjQRXBE67lXqPj8rqeo6VxcG8L5GmWgzVjz76CMMwGDVqFAMHDuTJJ58MPBYREUFcXFyrFyihobSiloSY5sHmCrdTUl57zOeUVdby1e4iDhS7cR5uAO2wWYkItxMTHc6B4hro53/u51kHeer1bRQdqgEgJTGSG381mIz0LidUp9cHg/vEs7fQjbvG36x6cJ94Djej+lHvS6SpFkM1JSUFgIceeoi4uLjAzyI/1PQ+UI2qaz3NbjPS+JwGr5et2UXkFVRQU+fFd3jNvcdrUAtU1zVgs1k4VFHLoYpaFr/5FZ9s899xwm6zcsVFvZlwSTphzhM/nx/XyX8t7Fm9v5+Uctc0EB559H0F875EmgrqrzIpKYldu3aRl5dH9+7dAcjLy2PdunX07duX8847r1WLlI6vcXYd/CO5xrXz/3VWUuA5yQkRvLQqm4JiN9X1XiwYgWWiNfXfNznxeA3yC6oIdxzk3Q05uGv8t4nu36MzN/96CD1Tfny/iWDqPJnniwQVqg8//DA5OTn8+te/DmxLSEjg8ccf54wzzmD58uWtVqCEhsbZ9a3ZxUesnd9XVMm6zXvZml1ERXU9DV4f9UfpZ9qocXt2vn8iKjLCwdRL+3PpeT2x2YK6tPpH1WnG80WCCtU9e/bQvXt3IiO/n411uVykpaWp56kEpCRGH/USqtUb89lbVEmYw0qFuw53jeeYgfpDvVNj+H//91wSO5u32ulodZr5fDm9BfWffcMwKCwspKGhIbCtoaGBwsLCYy4MEIHvZ88r3PWUVvi7QgXzF2O1WOgaF855g5JMDVSR1hZUqPbs2ZPy8nLuvvtuvv76a77++mvmzJlDWVkZZ5xxRmvXKCGstKKW+gYPhYeqKa2opbbuGNPsTbjC7MRGO6msrser/2hLiAnq8P/yyy/nz3/+M++//z7vv/9+YLvFYmH8+PGtVpyEtn1FlezeW0ZeQSXu6gZq6lsOVJvVvzy1utZDaUUd4U4rylQJNUGNVKdOncro0aMDN/5r/BozZgzXXHNNa9coIWhfUSVvrPmWgpIqKtx1xw3UqAg7nSKdHKqso6bO3+vUarFQ7q5vi3JFTBPUSNVms/HXv/6VzZs3s23bNsB/c76hQ4e2anESutZt3su+EjcNHh++FoabdpuV2CgnVTUNVNXUNXvMFe6gslqhKqHlhK6eHjp0qIJUgpKdX0ZUhIP9XgOfz8BqAcOg2SRVTKQTLP7zrr4f5K7/nlEQ/YM7n4p0dMcM1XvuuYcePXpw4403HrWRSiOLxcKDDz7YKsVJCDs8Oq2t8+DzNQ9Tp8NKTGQYFe566hqOflrAYbcQExVGj2Rzbiwp0laOGapvvPEGGRkZ3HjjjbzxxhtH7f7T2GxFoSo/1K9HZz7alEdNk4v8LRaIjQrDZxgUl9cccxLKagFXhIPIcKd6nErIOWaoduvWjcTExMD3IsHamVvCv7buo/DQ901Hwp02ol0Oyqvqqff4Wng1YIFol4PLL+6li+4l5BwzVNesWXPU70WOxTAM3lj3LS+u3Bk4rLdZLXSODqPe46Oo7PidnSLDbaR2iaZnUie6xh29n6pIR6a2/WKKghI3i17bxtbsIsB/qB/XKYyoCAeHKuuorfNis/pb7x1NmMNKapcoLj3Pv5jEXdOgnqUSklqcqAqGzqme3jxeH299vJsXV31DfYM/MTtHh9G9SxRVtQ3sLXRjt3H4rqU2LF5foDOVFbDa/JcFdIt3kdLl+wBVz1IJVS1OVLV0awrQRNXpblf+IZ58eSs5ByoA//LSnt38zUeqqus5VFVHlMuOu6YBh82KzWrBZ/iIdNgJd1qJjPDfl6rB46XWY5DW5N5S6lkqoarFiaqmiouLqa+vJybGf4lLeXk5drudrl27tm6F0uHkFZTzzBvb+erbYgz815ReNDSVLp0jiHBa+Wp3KWEOO13jXBSX1eDx+OiT1pkucS5yD1TgCrNRW++ltt6L02HDFWanpLwGh92GYRjqWSohLaiJqnXr1jFr1iyeffZZzj//fAA2bNjAjBkzdI+q08y+okqeeyeLL78tBqBTpJOh/bryf0b25qvdpdTUehjQM478wirqPf6b9w0/M5kplw4AYMWGHGrrmnfSd9c0UFvvITzMrp6lEvKCmqh65JFHSEtLCwQqwPnnn0+PHj144oknuPTSS1utQOlYtmYX0z0pmuLyGrrGuRjavwv1DV6+/LY00CU/yuXgzF7xgRHnxUNTA68/Vid93Z1UThVBNVTJz89nz549fPrpp4FtGzduZM+ePezbt6/VipOOp7SilqR4F7+8sBfnnZWM1WrB6bBxqKI20CW/ccQZHmY/IiyDeY5IKAtqpNqnTx+ysrK49tprm51TBRg4cGDrVScdTtMb4fkOL9hvOqkUTJd8ddKXU1lQI9U//OEPREZGYhgGZWVllJWVYRgGLpeLuXPntnaN0oFkpCdQVd2Au6YBwzBw1zRQVd2g5aQihwU1Uj377LNZtWoVS5cuJTs7G4D09HSmTJlCXFxcqxYoHYtuhCfSsqBXVMXFxXHLLbe0Zi0SInT4LnJsQYfq/v37eeaZZ9iyZQs9e/bk2muvZcOGDYwZM4a+ffu2Zo0iIiEjqFDNzc1lwoQJlJeXB86l2mw2Fi5cSFlZmc6riogcFtRE1WOPPUZZWVmz1VODBw8mOjqazz77zNSCFi5cSL9+/QLnbkVEQklQofrpp58SExPDihUrmm1PTk6moKDAtGK+/vprtm7dSkpKimn7FBFpS0GFanV1NUlJSURGNu9vWVdXR22tOaHF9zIAABOoSURBVJ2E6uvruf/++7nvvvtM2Z+ISHsIKlS7devGt99+y+effx7Ytm7dOnJzc00bVT7xxBOMGzeO1NTU4z9ZRKSDCipUx4wZg9frZerUqVgsFrZt28aMGTOwWCyMGTPmpIvYsmUL27dvZ/LkySe9LxGR9hRUqM6YMYPBgwdjGEazrzPPPJPf/va3J13Epk2b2L17NyNHjiQzM5OCggKmTZvGJ598ctL7FhFpS0FdUhUREcGLL77IihUr2LZtG+Cf/b/ssstwOE7+vuw33HADN9xwQ+DnzMxMnn76adLT00963yIibem4oVpfX8/s2bMJCwvj0UcfZfz48W1Rl4hISDpuqDqdTv7973+TlpZ23NurmEV3bxWRUBXUOdULL7yQvXv3UlFR0dr1iIiEtKDOqQ4ePJi1a9cyYcIErrjiChITE5uNWi+//PJWK1BEJJQEfTsVi8XCnj17ePzxx5s9ZrFYFKoiIocF3aXKMIzWrENE5JQQVKh+9NFHrV2HiMgpIahQVYMTEZHgtDj7bxgG8+fPZ/jw4Zx77rk89NBDOg0gItKCFkP15Zdf5rnnnqOiooKKigqWLFnCyy+/3Fa1iYiEnBZD9bXXXgMgKSmJ5ORkDMMIbBMRkSO1eE41Pz+fmJgY3nvvPXw+H5mZmeTn57dVbSIiIafFkWp5eTk9evQgIiKCyMhIunfvrlVVIiItOO7sv8fj4cCBAxiGgcfjAQj83Khbt26tV6GISAg5bqhmZWWRmZnZbFvTny0WCzt27DC/MhGREHTcUNUlVCIiwWsxVK+44oq2qkNE5JTQYqg+9NBDbVWHiMgpIah+qiIiEhyFqoiIiRSqIiImUqiKiJhIoSoiYiKFqoiIiRSqIiImUqiKiJhIoSoiYiKFqoiIiRSqIiImUqiKiJhIoSoiYiKFqoiIiRSqIiImUqiKiJhIoSoiYiKFqoiIiRSqIiImUqiKiJhIoSoiYqIW76baVg4dOsTvfvc78vLycDqd9OjRg/vvv5+4uLj2Lk1E5IR0iJGqxWLh+uuvZ+XKlbzzzjukpaXx6KOPtndZIiInrEOEamxsLMOHDw/8nJGRwf79+9uxIhGRH6dDhGpTPp+PZcuWkZmZ2d6liIicsA4XqvPmzcPlcnH11Ve3dykiIiesQ0xUNZo/fz65ubk8/fTTWK0dLu9FRI6rw4TqY489xvbt21m8eDFOp7O9yxER+VE6RKju2rWLZ555hp49ezJx4kQAUlNTWbRoUTtXJiJyYjpEqPbt25edO3e2dxkiIidNJy5FREykUBURMZFCVUTERApVERETKVRFREykUBURMZFCVUTERApVERETKVRFREykUBURMZFCVUTERApVERETKVRFREykUBURMZFCVUTERApVERETKVRFREykUBURMZFCVUTERApVERETKVRFREykUBURMZFCVUTERApVERETKVRFREykUBURMZFCVUTERApVERETKVRFREykUBURMZFCVUTERApVERETKVRFREykUBURMZFCVUTERApVERETdZhQzcnJYcKECYwZM4YJEyawZ8+e9i5JROSEdZhQvffee5k8eTIrV65k8uTJ/PGPf2zvkkRETpi9vQsAKCkpYceOHTz33HMAjB07lnnz5lFaWkpcXFyLr/V6vQAUFBS0ep0icvpozJTGjAlWhwjVAwcO0LVrV2w2GwA2m40uXbpw4MCB44ZqUVERAFOmTGn1OkXk9FNUVESPHj2Cfn6HCNWTceaZZ7J06VISExMDoSwicrK8Xi9FRUWceeaZJ/S6DhGqycnJHDx4EK/Xi81mw+v1UlhYSHJy8nFfGx4ezrBhw9qgShE53ZzICLVRh5ioio+PZ8CAAbz77rsAvPvuuwwYMOC4h/4iIh2NxTAMo72LANi9ezdz5syhoqKCTp06MX/+fHr16tXeZYmInJAOE6oiIqeCDnH4LyJyqlCoioiYSKEqImIihaqIiIlCOlRDtQnLoUOHmD59OmPGjOGXv/wlM2fOpLS0tL3LOiELFy6kX79+ZGdnt3cpQamrq+Pee+9l9OjR/PKXv+QPf/hDe5cUtLVr13L55Zczfvx4xo0bx6pVq9q7pKOaP38+mZmZR/xdhMLn9Gi1/+jPqRHCpk6darz55puGYRjGm2++aUydOrWdKwrOoUOHjE8//TTw85///GfjnnvuaceKTsz27duNadOmGSNGjDB27tzZ3uUEZd68ecZ///d/Gz6fzzAMwygqKmrnioLj8/mMYcOGBf5/zsrKMjIyMgyv19vOlR1p06ZNxv79+4/4uwiFz+nRav+xn9OQHak2NmEZO3Ys4G/CsmPHjpAY8cXGxjJ8+PDAzxkZGezfv78dKwpefX09999/P/fdd197lxI0t9vNm2++yW233YbFYgEgISGhnasKntVqpbKyEoDKykq6dOmC1drxPrrDhg07YhVkqHxOj1b7j/2cdohlqj/GyTRh6Uh8Ph/Lli0jMzOzvUsJyhNPPMG4ceNITU1t71KClp+fT2xsLAsXLmTjxo1ERkZy2223hcTyZovFwoIFC7jppptwuVy43W4WL17c3mUF7XT8nHa8/9ydZubNm4fL5eLqq69u71KOa8uWLWzfvp3Jkye3dyknxOv1kp+fz8CBA1m+fDl33nknt9xyC1VVVe1d2nF5PB6eeeYZnnrqKdauXcvf/vY3Zs2ahdvtbu/STisn8jkN2VBt2oQFOKEmLB3F/Pnzyc3NZcGCBR3ycO6HNm3axO7duxk5ciSZmZkUFBQwbdo0Pvnkk/YurUXJycnY7fbAIeiQIUPo3LkzOTk57VzZ8WVlZVFYWMjQoUMBGDp0KBEREezevbudKwvO6fg57fif5GMI9SYsjz32GNu3b2fRokU4nc72LicoN9xwA5988glr1qxhzZo1JCUl8eyzz3LBBRe0d2ktiouLY/jw4WzYsAHwz0aXlJT8qA5EbS0pKYmCggK+++47wN8jo6SkhO7du7dzZcE5HT+nIb32P1SbsOzatYuxY8fSs2dPwsPDAUhNTWXRokXtXNmJyczM5OmnnyY9Pb29Szmu/Px8fv/731NWVobdbmfWrFlcdNFF7V1WUN5++23+53/+JzDJduuttzJq1Kh2rupIDzzwAKtWraK4uJjOnTsTGxvLihUrQuJzerTaFyxY8KM+pyEdqiIiHU3IHv6LiHREClURERMpVEVETKRQFRExkUJVRMREClVpMxs3bqRfv37069ePjRs3tnc5rWL58uWB97h37972LkfaQciu/T+dzZkzhzfeeOOoj40cOZKnnnqqjSsKTlRUFEOGDAl83xFNnTqVzz77jHPPPZcXXnihvcsB/NcD79u3j5SUFNasWdPssfXr1/PSSy/x5ZdfUlZWRkxMDGeccQaXXnppYEllS38vH3/8MUlJSYGfX331VV544QVycnICt3+//fbbQ+Ja5I5CoRriBgwY0GylxxlnnNGO1RxbfX09gwYN4pVXXmnvUk4Z999/P0uXLgXAbreTmppKQ0MDn3/+Od98880R69S7du3aLECBZn87Tz31FE888QTgv8i9rKyMNWvWsHHjRl599VV69+7dyu/oFNEqzQmlVd19991Genq6kZ6ebuTn5x/1OcuWLTPS09ON/v37G5s2bTIMwzA2b95s9O/f30hPTzeef/75ZvsaMWKE8eGHHxq/+MUvjEGDBhljx441/vWvfzXbZ15ennHXXXcZ559/vjFw4EDjZz/7mfHAAw8YlZWVgee8/vrrgdo++OAD46qrrjIGDRpkPPfcc8ann34aeKyxT2XTba+//rpx3XXXGWeddZYxZswYY926dUZ+fr4xbdo0Y8iQIcYll1xivPXWW81qKikpMe677z7j4osvNgYNGmT89Kc/NebMmWMUFhYGntP0dyxfvtyYMWOGMWTIEONnP/uZ8cwzzwSe1/icH369/vrrhmEYxp133mmMHj3aOPvss42BAwcaF154oTFnzpxmvVmbvv9j/dv88Hlr1641pk6dapx11lnGhRdeaDz77LPNnjtixIjAv9HRXn/11VcbBQUFgcfKysqMJUuWBH5u/Df+61//esx6SkpKjEGDBhnp6enGLbfcYhiGYRQUFBhnn322kZ6ebtx0003HfK00p3Oqp6iJEydyySWX4PP5uOeeeygpKeHuu+/G5/ORmZnJNddc0+z5hYWFzJo1C/D378zOzubGG28MNB3Jz8/nyiuv5K233sLtdtOnTx9KS0tZsmQJ1113HR6P54ga7rzzTvbu3UtaWlpQjSjuu+8+cnNzcTgc5OTkMGvWLH7zm9/w7bffEhYWRm5uLvfcc0+gc3x5eTkTJkzgxRdfpLi4mF69elFdXc3y5cuZNGkSFRUVR/yOP/zhD+zYsYOwsDAKCgr4y1/+wn/+8x/A32glMjISgMjISIYMGcKQIUMC69RXr17NoUOHSE1NJS0tjYMHD7J8+XJuuummIP9Vju7WW2/l4MGDREREcPDgQebPn8/y5ctbfM2yZcsAcDgcPProo3Tt2jXwWExMDFOnTj3iNc8//zxnnnkmF1xwAdOnT2fLli2Bx/7973/T0NAAwOjRowH/yDYjIwOADRs2BJqiSMsUqiFu5MiRgYmRfv36NfswPvDAAyQnJ5OXl8f48ePJy8uja9euPPjgg0fsp6GhgYULF7JixQpeeeUVbDYbDQ0Ngd6df/vb3ygrKyMhIYEPP/yQt956i5dffhmAbdu28cEHHxy1tvXr1/P+++8zZcqU476XSy65hNWrV7NgwQIAqqurSUpKYvXq1YHf5fF4ApNc//znP8nLy8PpdPL222/z9ttv88EHHxAeHk5+fn4geJq68MILWbNmDe+99x4OhwPwBwrAK6+8wqBBgwACpypeeeUVLr74YgCWLl3KZ599Fvg98+bNC7z/vLy8476/Y5kyZQorV67ko48+CjRKOd768l27dgH+0z1NA/VYHA4H8fHxpKSkUFRUxPr165kyZUqgyUzT5svx8fFHfF9TU9PhGkt3VDqnGuJ+eE61afef2NhYHnnkEaZOnUpRUREAjz76KJ07dz5iPzExMYHw6N+/P/369WPHjh3s3LkT8AcHQHFxMeeff/4Rr9+yZUugtV6j3/zmN82aEx/Pz3/+cwDS0tIC20aPHo3dbm/WUarxvTTWVF9fz6WXXnrUmn7oV7/6FVarlfj4eOLi4jh48CDFxcXHrQ38rQ/nzJlDbm4utbW1zR4rLCz80Z2jxo8fD/gn7zIzM/nHP/7B3r17qaqqMmVC77rrrmPu3LmBfX388cfccMMNeL1e/v73vx/137ORodYgJ0yhGuIWLlzYYhf+vXv3Nvtg7Nmzh3PPPfdH/76oqKijTlg0Hd00OtFblkRHRwP+SZcfbmvs0ARHftCdTicDBgw4Yn9H69nZqVOnwPeNvyeY4HjnnXcCI/yEhATS09Nxu92BvqZtfWjct29fvvzyS3JycigsLKRLly7HfO4PZ+4vuugiYmNjKSsrC4xQu3XrFni8pKQk8H3j6DQiIiJk2vW1Nx3+n8Jyc3O5//77AQKHtQ8++OBRGxyXl5fz8ccfA5CdnR0Yofbr1w+AwYMHA/4geuyxxwKHxv/85z+56aabGDdu3BH7bBqEraGxJp/Px7333huo6aWXXmL27NlMmDDhhPfZ2OLth531t27dCoDL5WLt2rW8+uqrR33PP8Y777wDQFVVFWvXrgX8s+8tjVInTZoE+E/b3HXXXRQWFgYeKysr43//938B/ymUv/3tb80O3devX09ZWVng9wCcd955gdMhjXdrPXjwYOB9n3/++UEdbYhGqiFv5syZzQ7/e/bsycMPP0xDQwOzZ8+murqas88+myVLlnDNNdewZcsWbr/9dl577bVmr3M6ndxyyy10796dvLw8vF4vDoeD6dOnAzBjxgzWrFlDWVkZl156KWeccQb19fUcOHCAuro6lixZ0ub3rbr66qtZvnw5+/bt48orr6RXr14YhsGBAweorq7moYceon///ie0zz59+rB+/Xq+/vprxo4di8vl4vHHHw/sp7q6mszMTCIjIwPBdLJefPFFVq9eTVlZWWCfM2bMaPE1v/rVr/jqq6948cUX+fTTTxkxYgRpaWl4PB7279+Py+UKTCAuWLCAv/71r6SmpmKz2QKTjw6HI/B74uPjufHGG3nyySdZuXIlI0eOpKysDLfbjcvl4vbbbzflvZ4ONFINcVlZWWzbti3w1TjCbOxY7nK5ePjhh3E6nTzyyCO4XC527tzJ/Pnzm+0nMTGRJ598EovFgs/no2/fvixatCjQTLh79+689tprXHHFFXTu3JnvvvuOiooKBgwYwM0330zfvn3b/L3Hxsby6quvMmXKFJKTk8nNzaWkpISePXty3XXX/ajTHNOmTePiiy8mOjqaXbt2sW3bNmpra/n1r3/N9ddfT3x8PG63m/T0dNPuKPvkk0/SrVs3ampq6NKlC3fddRdXXnnlcV937733snjxYjIzM4mNjQ2chx08eDC33XYb4D9sv/XWW8nIyKC6upq9e/eSkpLCz3/+c1577bVmNz+cOXMm999/P+np6Rw8eBCAESNGsGzZMvr06WPKez0dqEn1aa5xtc3RVutI61m+fDn33HMPAB999FFI3Z1WWqaRqoiIiRSqIiIm0uG/iIiJNFIVETGRQlVExEQKVREREylURURMpFAVETGRQlVExET/H37xFzfcRFTNAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 360x360 with 1 Axes>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# For more strict model building, you probably want 80% of the molecules as training set, 20% as test set"
      ],
      "metadata": {
        "id": "ttYMwHp14vOb"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.model_selection import train_test_split"
      ],
      "metadata": {
        "id": "JVYoY1dQ5Qo0"
      },
      "execution_count": 18,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=0.2)"
      ],
      "metadata": {
        "id": "mkwa5ffp4uPT"
      },
      "execution_count": 19,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "X_train.shape, Y_train.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5sasgXMs5W3-",
        "outputId": "7de42a84-c769-4b76-c8af-69e85d5893f2"
      },
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "((111, 255), (111,))"
            ]
          },
          "metadata": {},
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "The training set reduced from 139 to 111"
      ],
      "metadata": {
        "id": "5j8fcM-L5dUf"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "X_test.shape, Y_test.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "0a1BbRUZ5jBi",
        "outputId": "37213e8c-a764-4769-eec8-4123fd915952"
      },
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "((28, 255), (28,))"
            ]
          },
          "metadata": {},
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "model = RandomForestRegressor(n_estimators=100)\n",
        "model.fit(X_train, Y_train)\n",
        "r2 = model.score(X_train, Y_train)\n",
        "r2"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2hfdkNDK85Bh",
        "outputId": "bddcaa8b-6f15-4531-e805-7eb085e28719"
      },
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.8681832428534362"
            ]
          },
          "metadata": {},
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Let's see the 80% training plot"
      ],
      "metadata": {
        "id": "DNk06UCz-bDl"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "Y_pred1 = model.predict(X_train)"
      ],
      "metadata": {
        "id": "MZt1mfoN9CGk"
      },
      "execution_count": 27,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "import seaborn as sns\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "sns.set(color_codes=True)\n",
        "sns.set_style(\"white\")\n",
        "\n",
        "ax = sns.regplot(Y_train, Y_pred1, scatter_kws={'alpha':0.4})\n",
        "ax.set_xlabel('Experimental pIC50', fontsize='large', fontweight='bold')\n",
        "ax.set_ylabel('Predicted pIC50', fontsize='large', fontweight='bold')\n",
        "ax.set_xlim(0, 12)\n",
        "ax.set_ylim(0, 12)\n",
        "ax.figure.set_size_inches(5, 5)\n",
        "plt.show"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 416
        },
        "id": "XQ5vqC8X9Wz_",
        "outputId": "c44d9a9a-3961-4f4b-f403-0dc511698c05"
      },
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/seaborn/_decorators.py:43: FutureWarning: Pass the following variables as keyword args: x, y. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
            "  FutureWarning\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<function matplotlib.pyplot.show>"
            ]
          },
          "metadata": {},
          "execution_count": 28
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 360x360 with 1 Axes>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Let's have a look at the ability to predict the test set"
      ],
      "metadata": {
        "id": "NqJH27rv-HZ1"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "model = RandomForestRegressor(n_estimators=100)\n",
        "model.fit(X_train, Y_train)\n",
        "r2 = model.score(X_test, Y_test)\n",
        "r2"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "1lVXb7v85jHt",
        "outputId": "19bfded7-e73d-45a3-d96e-04bcecbbcbbc"
      },
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "-0.21828110797107936"
            ]
          },
          "metadata": {},
          "execution_count": 22
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "Y_pred = model.predict(X_test)"
      ],
      "metadata": {
        "id": "o2t3avx652nJ"
      },
      "execution_count": 23,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "import seaborn as sns\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "sns.set(color_codes=True)\n",
        "sns.set_style(\"white\")\n",
        "\n",
        "ax = sns.regplot(Y_test, Y_pred, scatter_kws={'alpha':0.4})\n",
        "ax.set_xlabel('Experimental pIC50', fontsize='large', fontweight='bold')\n",
        "ax.set_ylabel('Predicted pIC50', fontsize='large', fontweight='bold')\n",
        "ax.set_xlim(0, 12)\n",
        "ax.set_ylim(0, 12)\n",
        "ax.figure.set_size_inches(5, 5)\n",
        "plt.show"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 416
        },
        "id": "MvueUl1x57_S",
        "outputId": "55394212-bc5b-4608-cc58-4ec2d873f7a4"
      },
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/seaborn/_decorators.py:43: FutureWarning: Pass the following variables as keyword args: x, y. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
            "  FutureWarning\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<function matplotlib.pyplot.show>"
            ]
          },
          "metadata": {},
          "execution_count": 24
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 360x360 with 1 Axes>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# That is to say if we use 80% of the molecules to build a model, to predict the rest 20%, the model failed! It primally because the number of molecules in this training is too small, it not necessarily indicate the model itself is bad, maybe we just need a bit more time to get more data point."
      ],
      "metadata": {
        "id": "MKQUcra26O_G"
      }
    }
  ],
  "metadata": {
    "colab": {
      "collapsed_sections": [],
      "name": "5_build.ipynb",
      "provenance": []
    },
    "kernelspec": {
      "display_name": "Python 3",
      "language": "python",
      "name": "python3"
    },
    "language_info": {
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "file_extension": ".py",
      "mimetype": "text/x-python",
      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.8.5"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}